COR Brief
Agents & Automation

Langflow

Langflow is an open-source, Python-based framework designed for building AI applications such as agents, Retrieval-Augmented Generation (RAG) systems, and workflows through a visual drag-and-drop editor. It supports integration with major large language models (LLMs), vector databases, and AI tools, enabling users to connect components into flows that represent application workflows like chatbots or document analysis systems. Users can test flows interactively, deploy them as APIs or MCP servers, or export them as JSON for integration with other applications. Langflow also offers a desktop application for Windows and macOS that manages dependencies and updates automatically. The platform provides a visual builder interface alongside source code access for Python customization, multi-agent orchestration capabilities, and observability integrations with LangSmith and LangFuse. Deployment options include running locally with Python and uv, using Docker containers, or leveraging a free enterprise-grade cloud platform, although cloud deployment requires manual addition of LLM API keys.

Updated Feb 4, 2026freemium

Langflow is an open-source visual framework for building and deploying AI workflows using major LLMs and vector databases.

Pricing
Free
Category
Agents & Automation
Company
Interactive PresentationOpen Fullscreen ↗
01
Drag-and-drop components to create AI workflows without extensive coding.
02
Access and modify source code components using Python for advanced customization.
03
Test and refine AI flows step-by-step within an interactive environment.
04
Manage conversations and retrieval across multiple AI agents within workflows.
05
Deploy workflows as APIs, MCP servers, or export as JSON for integration.
06
Integrate with LangSmith and LangFuse for monitoring and analysis.
07
Available for Windows and macOS with automatic updates and dependency management.

Agentic AI Applications

Build AI agents that perform tasks autonomously using multi-agent orchestration.

Retrieval-Augmented Generation Systems

Create workflows that combine LLMs with vector databases for document analysis and information retrieval.

Chatbots and Conversational AI

Develop chatbots with customizable conversation flows and integration with various AI tools.

1
Install Langflow
Run uv pip install langflow -U ensuring Python 3.10–3.13 and uv are installed.
2
Start Langflow
Execute uv run langflow run and open http://127.0.0.1:7860 in your browser.
3
Use the Visual Editor
Drag and drop components to build your AI workflow.
4
Deploy or Export
Deploy your flow as an API or MCP server, or export it as JSON for integration.
5
Alternative Installation
Use Docker with sudo docker run -d -p 7860:7860 --name langflow langflowai/langflow:latest for Linux environments.
6
Desktop App
Download and install the Langflow Desktop app for Windows or macOS from the official website.
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Strategic Context for Langflow

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Pricing
Model: freemium
Free Open-Source Version
Free
  • Full access to the open-source framework
  • Local deployment with Python or Docker
  • Visual editor and Python customization
Enterprise-Grade Cloud Platform
Not specified
  • Cloud deployment
  • Requires manual addition of LLM API keys

Specific pricing details for paid plans are not publicly available.

Assessment
Strengths
  • Supports all major LLMs and vector databases out-of-the-box
  • Combines visual editor with Python source code customization
  • Enables quick deployment as API or MCP server
  • Includes pre-built templates and components for rapid prototyping
  • Offers a desktop app with automatic updates and dependency management
Limitations
  • Requires Python 3.10–3.13 and uv for local installation or Docker for Linux
  • Docker deployment on servers may require firewall adjustments for security
  • Cloud deployments require manual addition of LLM API keys